There is a continuing need to develop improved methods for predicting fluid flow characteristics of petroleum reservoir rock. The predictions are particularly important when evaluating hydrocarbon distribution and when evaluating enhanced recovery techniques such as water flood, water flood followed by miscible flood, and miscible flood.
Towards relating the petrology of reservoirs (pore geometry, surface areas of mineral phases and pores, pore throat size frequency distributions, etc.) to geophysical and petrophysical data, Dr. R. Ehrlich at the University of South Carolina developed a procedure known as Petrographic Image Analysis (PIA) to generate high quality quantitative data from thin sections or slices of reservoir rock. PIA is utilized to link reservoir characteristics as viewed in section to petrophysical measurements obtained down-hole or from core samples, it being presumed that a relationship exists between essentially two-dimensional views and the three-dimensional character of the pore system or complex.
PIA relies on computer-based image analysis using pattern recognition/classification programs. The images are acquired by digitizing, for example, the analog output signal of a video scanner attached to an optical microscope. In a manner analogous to remote sensing, the analog signal (representing a time varying voltage proportional to scene brightness as the raster scans the image) is "digitized" by sampling intensities only at some integral time increment resulting in a grid of points or picture elements called pixels. Pores at least as small as 0.3 microns can be detected.
In the image acquisition procedure, the voids, i.e., pore system, in a thin slice or section of the reservoir rock are filled, as by injection, with a blue-dyed epoxy. Accordingly, the cross-section to be imaged consists of the undyed mineral matter and the blue-dyed voids. A digital filter is employed to distinguish the pores (blue) from the surrounding rock formation (not blue) for image segmentation. By distinguishing the pores from the rock matrix in this manner, a binary image of the two-dimensional or planar surface of the thin section may be obtained wherein all pixels corresponding to pores are set to black (binary one, for example) while all others are set to white (binary zero). Binary images of this type have been utilized for subsequent analysis of pore geometry, pore throat size frequency distributions, etc. It is noted, however, that the imaged pores at the planar surface of the thin section are largely uncoordinated. That is, the imaged pores are mostly not connected to one another whereas in the three dimensional pore network narrow connections termed pore throats do connect the pores to one another. In binary images of the above noted type, the only imaged pore throats are the relatively few that exist at the surface of the thin section. Also relatively large pores may appear as two disconnected pores if a medial portion thereof is overlain by mineral at the surface of the thin section.
It is noted that most minerals in typical petroleum reservoir rock, e.g., sandstone, are translucent to transparent. Consequently, blue-eyed epoxy filled voids beneath the surface of the thin section can be viewed through the overlying mineral matter. Thus it has been possible to define pore overlain by mineral matter (and also pore underlain by mineral matter) by use of a digital filter as a function of hue, saturation and intensity of the blue-dyed epoxy filling the pores in the three-dimensional thin section. Other more complex digital filters may be used, for example, to distinguish clay from pore even if the clay is blue tinged or to distinguish carbonate textural types or detrital minerals by using gray-level segmentation.
A more complete and detailed disclosure of the foregoing imaging and digital filtering techniques and related analysis can be found in the 1983 Ph.D. Dissertation of Sterling James Crabtree, "Algorithmic Development of a Petrographic Image Analysis System", Department of Geology, University of South Carolina, Columbia, S.C.; and in Crabtree, Ehrlich and Prince, "Evaluation of Strategies for Segmentation of Blue-dyed Pores in Thin Sections of Reservoir Rocks" Computer Vision, Graphics, and Image Processing 28, 1-18 (1984).
In contrast to computer-based image analysis, analytical procedures have been developed wherein physical tests such as fluid displacement tests are performed on actual reservoir core samples. These tests, however, require a relatively large sample size and substantial time and money to complete. As an alternative, fluid flow displacement tests have been performed with artificially designed pore system configurations or standard materials such as homogeneous Berea sandstone, neither of which can reliably represent the specific pore structure of a complex reservoir having unique characteristcs. Consequently, many prior fluid flow models were of minimal predictive value because of errors and/or limitations inherent in the modeling processes utilized.
Disclosures of fluid displacement tests using micromodels and rock fluid transport theories can be found in Larsen, Scrivan and Davis, 1977, Percolation Theory of Residual Phases in Porous Media: Nature, Vol. 268, pp. 409-413; McKellar and Wardlaw, 1982, A Method of Making Two-Dimensional Glass Micromodels of Pore Systems: tech. note, Journal Canadian Petr. Tech., Vol. 21, No. 4; Morrow and Chatzie, 1981, Measurement and Correlation of Conditions for Entrapment and Mobilization of Residual Oil--Final Report: DOE/BETC/3251-12, U.S. Dept. Energy. October 1981, New Mexico Petroleum Recovery Research Center, New Mexico Inst. Mining and Technology, Socorro, N. Mex.; and Pathak, Winterfield, et al, 1980, Rock Structure and Transport Therein: Unifying with Voroni Models and Percolation Concepts: SPE 8846, First Joint SPE/DOE Symposium Enhanced Oil Recovery, Tulsa.
In the above referenced McKellar and Wardlaw paper, several methods of making micromodels are briefly discussed along with a detailed description of a technique developed by the authors. This latter technique uses photo-imaging of a synthesized or hand drafted pore system followed by chemical etching of the image in glass. The glass micromodel (termed a "two-dimensional" glass micromodel because the two-dimensional image of the synthesized pore system is carried into the third dimension by the etching process) is then used in a laboratory setting as a substitute rock-pore complex for viewing and evaluation of fluid movement. Quantitative results are typically reported using mass balance or chromatography procedures, but the results are presented strictly in terms of the micromodel itself which heretofore could not be reliably related independently of the skill of the model maker to actual and specific rock-pore systems that exist in nature.